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He W.-P.,National Climate Center | Wang L.,Beijing Institute of Technology | Jiang Y.-D.,National Climate Center | Wan S.-Q.,Yangzhou Meteorological Office
Theoretical and Applied Climatology | Year: 2015

Parameter estimation is an important research topic in nonlinear dynamics. Based on the evolutionary algorithm (EA), Wang et al. (2014) present a new scheme for nonlinear parameter estimation and numerical tests indicate that the estimation precision is satisfactory. However, the convergence rate of the EA is relatively slow when multiple unknown parameters in a multidimensional dynamical system are estimated simultaneously. To solve this problem, an improved method for parameter estimation of nonlinear dynamical equations is provided in the present paper. The main idea of the improved scheme is to use all of the known time series for all of the components in some dynamical equations to estimate the parameters in single component one by one, instead of estimating all of the parameters in all of the components simultaneously. Thus, we can estimate all of the parameters stage by stage. The performance of the improved method was tested using a classic chaotic system—Rössler model. The numerical tests show that the amended parameter estimation scheme can greatly improve the searching efficiency and that there is a significant increase in the convergence rate of the EA, particularly for multiparameter estimation in multidimensional dynamical equations. Moreover, the results indicate that the accuracy of parameter estimation and the CPU time consumed by the presented method have no obvious dependence on the sample size. © 2015 Springer-Verlag Wien


He W.,National Climate Center | Wan S.,Yangzhou Meteorological Office | Jiang Y.,National Climate Center | Jin H.,Lanzhou University | And 3 more authors.
International Journal of Climatology | Year: 2013

An abrupt change occasionally occurs when the dynamical system suddenly shifts from one stable state to a new state, which can take place in many complex systems, such as climate, ecosystem, social system, and so on. In order to detect abrupt change, this article presents a novel method - sliding transformation parameter (STP) on the basis of skewness change and the Box-Cox transformation. Tests on model time series and 1000 simulated daily precipitation data show the ability of the present method to identify and detect abrupt change of probability density function. The applications of STP in daily precipitation data show that there is an abrupt climate change between 1979 and 1980 in the selected observational stations, which is almost the same with the result obtained by approximate entropy (ApEn). Furthermore, it is found that the sample sizes of sliding windows have some influence on the Lambda parameter of the Box-Cox transformation, but it does not significantly affect the varying trend of the parameter and the identification of the change point in annual or interannual time scale. Comparing STP with the coefficient of skewness and kurtosis, ApEn, and some statistics approaches (e.g. percentiles and annual maxima), we find that the performance of the present method is much better than that of these methods. © 2012 Royal Meteorological Society.


Wan S.,Yangzhou Meteorological Office | Wan S.,Yangzhou University | Hu Y.,Yangzhou Meteorological Office | You Z.,Yangzhou Meteorological Office | And 2 more authors.
International Journal of Climatology | Year: 2013

Using the generalized Pareto distribution (GPD) and a spatial scheme of parameter estimation, spatial patterns of extreme monthly precipitation (EMP) in China were studied using 740 stations' data from 1960 to 2007. The spatial patterns of EMP are described by the GPD's scale and shape parameters, whose regional features depend on ENSO activities. The results show that the scale parameter (representing variability) in monsoon areas, such as southern China, is greater than that of non-monsoon areas, such as northern China, and that it is greater in summer than that in autumn. The shape parameter (representing record-breaking probability) reaches a maximum in non-monsoon areas and a minimum in monsoon areas. For the time scale, record-breaking events would occur more easily in the seasons other than summer. The regional difference in terms of dependence of EMP's variability on Southern Oscillation (SO) was also related to the monsoon transition zone. The variability with great dependence on SO was in the Qinghai-Tibet Plateau and in the region between the Yangtze and Yellow rivers, which are dry-wet transition zones. The response of EMP's record-breaking probability to SO is apparent in most regions of China, and its spatial pattern becomes the largest in summer and much smaller in spring and autumn. © 2012 Royal Meteorological Society.


Wang L.,Beijing Institute of Technology | Wang L.,National Climate Center | He W.-P.,National Climate Center | Liao L.-J.,Beijing Institute of Technology | And 2 more authors.
Theoretical and Applied Climatology | Year: 2014

Parameter estimation is an important scientific problem in various fields such as chaos control, chaos synchronization and other mathematical models. In this paper, a new method for parameter estimation in nonlinear dynamical equations is proposed based on evolutionary modelling (EM). This will be achieved by utilizing the following characteristics of EM which includes self-organizing, adaptive and self-learning features which are inspired by biological natural selection, and mutation and genetic inheritance. The performance of the new method is demonstrated by using various numerical tests on the classic chaos model-Lorenz equation (Lorenz 1963). The results indicate that the new method can be used for fast and effective parameter estimation irrespective of whether partial parameters or all parameters are unknown in the Lorenz equation. Moreover, the new method has a good convergence rate. Noises are inevitable in observational data. The influence of observational noises on the performance of the presented method has been investigated. The results indicate that the strong noises, such as signal noise ratio (SNR) of 10 dB, have a larger influence on parameter estimation than the relatively weak noises. However, it is found that the precision of the parameter estimation remains acceptable for the relatively weak noises, e.g. SNR is 20 or 30 dB. It indicates that the presented method also has some anti-noise performance. © 2014 Springer-Verlag Wien.


He W.-P.,National Climate Center | Liu Q.-Q.,Nanjing University of Information Science and Technology | Jiang Y.-D.,National Climate Center | Lu Y.,Yangzhou Meteorological Office
Chinese Physics B | Year: 2015

In the present paper, a comparison of the performance between moving cutting data-rescaled range analysis (MC-R/S) and moving cutting data-rescaled variance analysis (MC-V/S) is made. The results clearly indicate that the operating efficiency of the MC-R/S algorithm is higher than that of the MC-V/S algorithm. In our numerical test, the computer time consumed by MC-V/S is approximately 25 times that by MC-R/S for an identical window size in artificial data. Except for the difference in operating efficiency, there are no significant differences in performance between MC-R/S and MC-V/S for the abrupt dynamic change detection. MC-R/S and MC-V/S both display some degree of anti-noise ability. However, it is important to consider the influences of strong noise on the detection results of MC-R/S and MC-V/S in practical application processes. © 2015 Chinese Physical Society and IOP Publishing Ltd.


Zhou G.,Yangzhou Meteorological Office | Wan S.,Yangzhou Meteorological Office | Feng G.,National Climate Center | He W.,National Climate Center
International Journal of Climatology | Year: 2012

Using generalised Pareto distribution (GPD) function, the regional characteristic of extreme monthly low temperatures (EMLT) distribution during 1960-2007 in China is studied, and the potential impact of climate warming on EMLT regions in China is analysed. The results show that EMLT space distribution has latitudinal difference in China. Higher-value EMLT events are likely to happen in northeastern and southwestern China, while EMLT variability and occurrence probability of high-value EMLT events are less in the Yangtze and Huaihe River basin and the coast of southern China. The study indicates that climate warming impacts EMLT, and EMLT distribution responds to the climate warming over most areas of China. © 2010 Royal Meteorological Society.


Wang L.,National Climate Center | Wang L.,Beijing Institute of Technology | He W.-P.,Beijing Institute of Technology | Wan S.-Q.,Yangzhou Meteorological Office | And 2 more authors.
Wuli Xuebao/Acta Physica Sinica | Year: 2014

On the basis of evolutionary algorithm, a novel method for parameter estimation of nonlinear dynamic equations is given in the present paper. Numerical tests indicate that the unknown parameters all can be estimated quickly and accurately whether the partial parameters are unknown or all parameters are unknown in the classic Lorenz equation. However, it is found that the convergence rate of the new algorithm is relatively slow when multiple unknown parameters are estimated simultaneously. To solve this problem, a corresponding improvement of measure is proposed, namely, a constraint mechanism is taken during the variation operation of evolutionary algorithm. The improvement is mainly based on the characteristic that the longer the running time of the evolutionary algorithm, the smaller the range of variation of the estimated parameters. Results indicate that the searching speed of the algorithm is greatly improved by using the improved estimation parameter project. © 2014 Chinese Physical Society.


He W.,National Climate Center | Feng G.,National Climate Center | Wu Q.,National Satellite Meteorological Center | He T.,Jinan Environmental Monitoring Center | And 2 more authors.
International Journal of Climatology | Year: 2012

On the basis of detrended fluctuation analysis (DFA), a new method, moving cut data-DFA (MC-DFA), was presented to detect abrupt dynamic change in correlated time series. The numerical tests show the capability of the presented method to detect abrupt change time-instants in model time series generated by Logistic map. Moving DFA (MDFA) and approximate entropy (ApEn) can provide some information such as a single time-instant of abrupt dynamic change, but both of them cannot exactly detect all of the abrupt change regions. Some traditional methods, such as moving t-test, Cramer method, Mann-Kendall test and Yamamoto method, even cannot provide any information of abrupt dynamic change in these model time series. Meanwhile, results showed that windows sizes and strong noise have some less effect on the MC-DFA results. In summary, MC-DFA provides a reliable measure to detect the abrupt dynamic change in correlated time series, and perfectively make up the deficiencies of MDFA and ApEn. The applications in daily surface air pressure records further verify the validity of the present method. © 2011 Royal Meteorological Society.


Wan S.-Q.,Lanzhou University | Gu C.-H.,Yangzhou Meteorological Office | Kang J.-P.,Yangzhou Meteorological Office | Zou J.-X.,Yangzhou Meteorological Office | And 2 more authors.
Wuli Xuebao/Acta Physica Sinica | Year: 2010

Based on monthly data from 1960 to 2007 of 740 stations in China, we investigate the response of monthly extreme high-temperature (MEHT) to atmospheric oscillation through spatial Generalized Pareto Distribution (GPD) model. Here we take different groupings of North Atlantic Oscillation (NAO) and Southern Oscillation (SO) as forcing parameters in the model and evaluate the response of MEHT to atmospheric oscillation in 9 different scenarios. Results show that the impact of NAO/SO on MEHT of China is significant and different widely among different regions, i.e. the regions showing significant dependence of MEHT on atmospheric oscillation are Northeast China, the eastern part of the Tibetan Plateau, reaches of Yangtze and Yellow river and part of South China. To be specific, 1) MEHT obviously dependent on NAO is the north-east areas, followed by the eastern Tibet Plateau; MEHT obviously dependent on SO is mainly the Eastern Tibet Plateau and the Yangtze River and Yellow River and etc.; 2) Nonlinear addition effect of NAO and SO is not obvious, their impact on MEHT is mainly one-way, that is, both acting as forcing factors, most of the region forced by them is not significantly weakened or strengthened, and the reason may be related to differences in the atmosphere oscillation spatial and temporal distribution. © Chin.Phys.Soc.


He W.-P.,National Climate Center | Wang L.,Beijing Institute of Technology | Wan S.-Q.,Yangzhou Meteorological Office | Liao L.-J.,Beijing Institute of Technology | He T.,Jinan Environment Protection Monitoring Center
Wuli Xuebao/Acta Physica Sinica | Year: 2012

A new method of predicting dryness and wetness based on evolutionary modeling (EM) is presented in this paper. Numerical tests indicate that the basic dynamic characteriscs can be captured by EM and the model obtained by EM is not only able to preferablely simulate historical evolution, but also can exactly predict the future evolutionary trend of a time series. For the model obtained by EM with relatively larger prediction errors, the secondary EM can improve the prediction accuracy obviously. © 2012 Chinese Physical Society.

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